Urban ozone (O 3 ) pollution is influenced by the transport of wildfire smoke but observed impacts are highly variable. We investigate O 3 impacts from smoke in 18 western US cities during July−September, 2013− 2017, with ground-based monitoring data from air quality system sites, using satellite-based hazard mapping system (HMS) fire and smoke product to identify overhead smoke. We present four key findings. First, O 3 and PM 2.5 (particulate matter <2.5 μm in diameter) are elevated at nearly all sites on days influenced by smoke, with the greatest mean enhancement occurring during multiday smoke events; nitrogen oxides (NO x ) are not consistently elevated across all sites. Second, PM 2.5 and O 3 exhibit a nonlinear relationship such that O 3 increases with PM 2.5 at low to moderate 24 h PM 2.5 , peaks around 30−50 μg m −3 , and declines at higher PM 2.5 . Third, the rate of increase of morning O 3 is higher and NO/NO 2 ratios are lower on smoke-influenced days, which could result from additional atmospheric oxidants in smoke. Fourth, while the HMS product is a useful tool for identifying smoke, O 3 and PM 2.5 are elevated on days before and after HMS-identified smoke events implying that a significant fraction of smoke events is not detected.
We utilize the NOAA Hazard Mapping System smoke product for the period of 2005 to 2016 to develop climatology of smoke occurrence over the Continental United States (CONUS) region and to study the impact of wildland fires on particulate matter air quality at the surface. Our results indicate that smoke is most frequently found over the Great Plains and western states during the summer months. Other hotspots of smoke occurrence are found over state and national parks in the southeast during winter and spring, in the Gulf of Mexico southwards of the Texas and Louisiana coastline during spring season and along the Mississippi River Delta during the fall season. A substantial portion (20%) of the 24 h federal standard for particulate pollution exceedance events in the CONUS region occur when smoke is present. If the U.S. Environmental Protection Agency regulations continue to reduce anthropogenic emissions, wildland fire emissions will become the major contributor to particulate pollution and exceedance events. In this context, we show that HMS smoke product is a valuable tool for analysis of exceptional events caused by wildland fires and our results indicate that these tools can be valuable for policy and decision makers.
Wildfires emit O precursors but there are large variations in emissions, plume heights, and photochemical processing. These factors make it challenging to model O production from wildfires using Eulerian models. Here we describe a statistical approach to characterize the maximum daily 8-h average O (MDA8) for 8 cities in the U.S. for typical, nonfire, conditions. The statistical model represents between 35% and 81% of the variance in MDA8 for each city. We then examine the residual from the model under conditions with elevated particulate matter (PM) and satellite observed smoke ("smoke days"). For these days, the residuals are elevated by an average of 3-8 ppb (MDA8) compared to nonsmoke days. We found that while smoke days are only 4.1% of all days (May-Sept) they are 19% of days with an MDA8 greater than 75 ppb. We also show that a published method that does not account for transport patterns gives rise to large overestimates in the amount of O from fires, particularly for coastal cities. Finally, we apply this method to a case study from August 2015, and show that the method gives results that are directly applicable to the EPA guidance on excluding data due to an uncontrollable source.
We analyze the effect of precipitation type on mercury wet deposition using a new database of individual rain events spanning the contiguous United States. Measurements from the Mercury Deposition Network (MDN) containing single rainfall events were identified and classified into six precipitation types. Mercury concentrations in surface precipitation follow a power law of precipitation depth that is modulated by precipitation system morphology. After controlling for precipitation depth, the highest mercury deposition occurs in supercell thunderstorms, with decreasing deposition in disorganized thunderstorms, quasi-linear convective systems (QLCS), extratropical cyclones, light rain, and land-falling tropical cyclones. Convective morphologies (supercells, disorganized, and QLCS) enhance wet deposition by a factor of at least 1.6 relative to nonconvective morphologies. Mercury wet deposition also varies by geographic region and season. After controlling for other factors, we find that mercury wet deposition is greater over high-elevation sites, seasonally during summer, and in convective precipitation.
Extensive expansion in irrigated agriculture has taken place over the last half century. Due to increased irrigation and resultant land use land cover change, the central United States has seen a decrease in temperature and changes in precipitation during the second half of 20th century. To investigate the impacts of widespread commencement of irrigation at the beginning of the growing season and continued irrigation throughout the summer on local and regional weather, the Great Plains Irrigation Experiment (GRAINEX) was conducted in the spring and summer of 2018 in southeastern Nebraska. GRAINEX consisted of two, 15-day intensive observation periods. Observational platforms from multiple agencies and universities were deployed to investigate the role of irrigation in surface moisture content, heat fluxes, diurnal boundary layer evolution, and local precipitation.This article provides an overview of the data collected and an analysis of the role of irrigation in land-atmosphere interactions on time scales from the seasonal to the diurnal. The analysis shows that a clear irrigation signal was apparent during the peak growing season in mid-July. This paper shows the strong impact of irrigation on surface fluxes, near-surface temperature and humidity, as well as boundary layer growth and decay.
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